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This paper is in the following e-collection/theme issue:

Artificial Intelligence in Surgery and Perioperative Medicine (94) New Methods (1831) Tools, Programs and Algorithms (597) Decision Support for Health Professionals (2294)

Published on in Vol 5, No 1 (2022): Jan-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/37174, first published .
Patient undergoing surgery with medical devices attached

Demonstration and Performance Evaluation of Two Novel Algorithms for Removing Artifacts From Automated Intraoperative Temperature Data Sets: Multicenter, Observational, Retrospective Study

Demonstration and Performance Evaluation of Two Novel Algorithms for Removing Artifacts From Automated Intraoperative Temperature Data Sets: Multicenter, Observational, Retrospective Study

Authors of this article:

Amit Bardia1 Author Orcid Image ;   Ranjit Deshpande2 Author Orcid Image ;   George Michel2 Author Orcid Image ;   David Yanez2 Author Orcid Image ;   Feng Dai2 Author Orcid Image ;   Nathan L Pace3 Author Orcid Image ;   Kevin Schuster4 Author Orcid Image ;   Michael R Mathis5 Author Orcid Image ;   Sachin Kheterpal5 Author Orcid Image ;   Robert B Schonberger2 Author Orcid Image
Article Authors Cited by (2) Tweetations (3) Metrics

Journals

  1. Piper I, Donald R, Sandall K, Docherty A. Accelerometers improve detection of movement related artifact in bedside ICU data. Journal of Clinical Monitoring and Computing 2026 View
  2. Liu Y, Zhao Q, Li K, Dowding D. Continuous Temperature Monitoring via Wearable Devices for Fever or Infection Management in Acute Care Hospitals: Scoping Review of Clinical Implementation and Data Analytics. JMIR mHealth and uHealth 2026;14:e89773 View